Hallmann, J., Kolossa, S., Celis-Morales, C., Forster, H., O’Donovan, C. B., Woolhead, C., Macready, A. L.
ORCID: https://orcid.org/0000-0003-0368-9336, Fallaize, R., Marsaux, C. F. M., Tsirigoti, L., Efstathopoulou, E., Moschonis, G., Navas-Carretero, S., San-Cristobal, R., Godlewska, M., Surwiłło, A., Mathers, J. C., Gibney, E. R., Brennan, L., Walsh, M. C., Lovegrove, J. A.
ORCID: https://orcid.org/0000-0001-7633-9455, Saris, W. H. M., Manios, Y., Martinez, J. A., Traczyk, I., Gibney, M. J. and Daniel, H.
(2015)
Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP.
Molecular Nutrition and Food Research, 59 (12).
pp. 2565-2573.
ISSN 1613-4125
doi: 10.1002/mnfr.201500414
Abstract/Summary
SCOPE: A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. METHODS AND RESULTS: We used mathematical modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Amongst other food items, fish, pizza, chicken and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set.
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| Item Type | Article |
| URI | https://reading-pure-test.eprints-hosting.org/id/eprint/42874 |
| Identification Number/DOI | 10.1002/mnfr.201500414 |
| Refereed | Yes |
| Divisions | Central Services Life Sciences > School of Agriculture, Policy and Development > Department of Agri-Food Economics & Marketing Life Sciences > School of Chemistry, Food and Pharmacy > Department of Food and Nutritional Sciences |
| Download/View statistics | View download statistics for this item |
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